Block adaptive selection of multiple core transforms for video coding

Santiago De-Luxán-Hernández, Detlev Marpe, Heiko Schwarz, Klaus Robert Müller, Mathias Wien, Jens Rainer Ohm, Thomas Wiegand

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Transform coding tools in video coding have traditionally relied on the Discrete Cosine Transform Type II (DCT-II) to map residual signals to a new domain where quantization and entropy coding tools achieve a better coding efficiency than in the spatial domain. However, the DCT-II is not sufficient to model all different types of residual signals efficiently, especially in the intra-predicted blocks case. For this reason, the DST-VII was introduced in H.265/High Efficiency Video Coding (HEVC) in order to improve the compression performance of 4 × 4 intra-predicted blocks. In this paper we propose a multiple core transform approach, in which each transform is separable and generated by combining two one-dimensional transforms for the vertical and horizontal directions. The pair of 1-D transforms is selected from a set of three different types of Discrete Trigonometric Transforms and the Identity Transformation. Test results show that the proposed algorithm achieves bit rate reductions of 3% on average with respect to HEVC for intra-predicted residuals.

Original languageEnglish
Title of host publication2016 Picture Coding Symposium, PCS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509059669
DOIs
Publication statusPublished - 2017 Apr 19
Externally publishedYes
Event2016 Picture Coding Symposium, PCS 2016 - Nuremberg, Germany
Duration: 2016 Dec 42016 Dec 7

Publication series

Name2016 Picture Coding Symposium, PCS 2016

Other

Other2016 Picture Coding Symposium, PCS 2016
Country/TerritoryGermany
CityNuremberg
Period16/12/416/12/7

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

  • Discrete Trigonometric Transforms
  • Intra Coding
  • Multiple Transforms
  • Separable Transforms
  • Transform Coding

ASJC Scopus subject areas

  • Media Technology
  • Signal Processing

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